code: def test_shard_sampler(self):
      for n_elements in [64, 123]:
          dataset = list(range(n_elements))
  
          self.check_shard_sampler(
              dataset, 4, drop_last=True, num_processes=2
          )
          self.check_shard_sampler(
              dataset, 4, drop_last=False, num_processes=2
          )
  
          self.check_shard_sampler(
              dataset, 4, drop_last=True, num_processes=3
          )
          self.check_shard_sampler(
              dataset, 4, drop_last=False, num_processes=3
          )
  
imports: import copy
  import unittest
  import numpy
  from transformers.data.data_collator import default_data_collator
  from transformers.testing_utils import require_accelerate, require_torch
  from transformers.trainer_utils import RemoveColumnsCollator, find_executable_batch_size
  from transformers.utils import is_torch_available
label_desc: Use image node_id 15 for calling the TrainerUtilsTest obj's underlying member method code with example usage: obj.test_shard_sampler() without return types